Exploiting data semantics to discover, extract, and model web sources

We describe DEIMOS, a system that automatically discovers and models new sources of information. The system exploits four core technologies developed by our group that makes an end-to-end solution to this problem possible. First, given an example source, DEIMOS finds other similar sources online. Second, it invokes and extracts data from these sources. Third, given the syntactic structure of a source, DEIMOS maps its inputs and outputs to semantic types. Finally, it infers the source’s semantic definition, i.e., the function that maps the inputs to the outputs. DEIMOS is able to successfully automate these steps by exploiting a combination of background knowledge and data semantics. We describe the challenges in integrating separate components into a unified approach to discovering, extracting and modeling new online sources. We provide an end-toend validation of the system in two information domains to show that it can successfully discover and model new data sources in those domains. 1

Automated recognition of malignancy mentions in biomedical literature

BACKGROUND: The rapid proliferation of biomedical text makes it increasingly difficult for researchers to identify, synthesize, and utilize developed knowledge in their fields of interest. Automated information extraction procedures can assist in the acquisition and management of this knowledge. Previous efforts in biomedical text mining have focused primarily upon named entity recognition of well-defined molecular objects such as genes, but less work has been performed to identify disease-related objects and concepts. Furthermore, promise has been tempered by an inability to efficiently scale approaches in ways that minimize manual efforts and still perform with high accuracy. Here, we have applied a machine-learning approach previously successful for identifying molecular entities to a disease concept to determine if the underlying probabilistic model effectively generalizes to unrelated concepts with minimal manual intervention for model retraining. RESULTS: We developed a named entity recognizer (MTag), an entity tagger for recognizing clinical descriptions of malignancy presented in text. The application uses the machine-learning technique Conditional Random Fields with additional domain-specific features. MTag was tested with 1,010 training and 432 evaluation documents pertaining to cancer genomics. Overall, our experiments resulted in 0.85 precision, 0.83 recall, and 0.84 F-measure on the evaluation set. Compared with a baseline system using string matching of text with a neoplasm term list, MTag performed with a much higher recall rate (92.1% vs. 42.1% recall) and demonstrated the ability to learn new patterns. Application of MTag to all MEDLINE abstracts yielded the identification of 580,002 unique and 9,153,340 overall mentions of malignancy. Significantly, addition of an extensive lexicon of malignancy mentions as a feature set for extraction had minimal impact in performance. CONCLUSION: Together, these results suggest that the identification of disparate biomedical entity classes in free text may be achievable with high accuracy and only moderate additional effort for each new application domain

Complementary and alternative medicine use among women at increased genetic risk of breast and ovarian cancer

<p>Abstract</p> <p>Background</p> <p>Complementary and alternative medicine (CAM) use is well documented among breast cancer patients and survivors, but little evidence is available to describe rates and patterns of use among women at increased genetic risk of breast cancer.</p> <p>Methods</p> <p>A pre-visit telephone interview was conducted to ascertain CAM use among the <it>BRCA </it>mutation carriers enrolled in a high-risk breast cancer screening study. Participants were asked to report on their use of thirteen therapies within the year prior to enrollment into the study. Logistic regression was used to evaluate the association between various factors and CAM use in this population.</p> <p>Results</p> <p>Among the 164 <it>BRCA1 </it>or <it>BRCA2 </it>mutation-positive (<it>BRCA</it>+) women in this analysis, 78% reported CAM use, with prayer and lifestyle diet being the two most commonly reported modalities. Many subjects used multiple CAM therapies, with 34% reporting use of three or more modalities. The most commonly used modalities were mind-body therapies and biologically-based practices, 61.6% and 51.8%, respectively. High-risk women were more likely to use CAM if they were older, more educated, more worried about ovarian cancer risk, or had a previous cancer diagnosis.</p> <p>Conclusion</p> <p>This study suggests that the prevalence of CAM use is high among <it>BRCA </it>mutation carriers, with frequency of use comparable to that of breast cancer patients and survivors. Given the high prevalence of CAM use in our subjects, especially biologically-based therapies including herbal supplements, whose safety and efficacy in relation to cancer risk are unknown, our study suggests that future research is necessary to clarify these risks, and that it is important for providers to inquire about and to discuss the pros and cons of CAM use with their <it>BRCA+ </it>patients.</p

Factors associated with testicular self-examination among unaffected men from multiple-case testicular cancer families

<p>Abstract</p> <p>Background</p> <p>The lifetime testicular cancer (TC) risk in the general population is relatively low (~1 in 250), but men with a family history of TC are at 4 to 9 times greater risk than those without. Some health and professional organizations recommend consideration of testicular self-examination (TSE) for certain high-risk groups (e.g. men with a family history of TC). Yet little is known about factors associated with TSE behaviors in this at-risk group.</p> <p>Methods</p> <p>We collected information on this subject during an on-going NCI multidisciplinary, etiologically-focused, cross-sectional Familial Testicular Cancer (FTC) study. We present the first report specifically targeting TSE behaviors among first- and second-degree relatives (n = 99) of affected men from families with ≥ 2 TC cases. Demographic, medical, knowledge, health belief, and psychological factors consistent with the Health Belief Model (HBM) were evaluated as variables related to TSE behavior, using chi-square tests of association for categorical variables, and t-tests for continuous variables.</p> <p>Results</p> <p>For men in our sample, 46% (n = 46) reported performing TSE regularly and 51% (n = 50) reported not regularly performing TSE. Factors associated (p < .05) with regularly performing TSE in multivariate analysis were physician recommendation and testicular cancer worry. This is the first study to examine TSE in unaffected men from FTC families.</p> <p>Conclusion</p> <p>The findings suggest that, even in this high-risk setting, TSE practices are sub-optimal. Our data provide a basis for further exploring psychosocial issues that are specific to men with a family history of TC, and formulating intervention strategies aimed at improving adherence to TSE guidelines.</p

De novo mutations in GRIN1 cause extensive bilateral polymicrogyria

Polymicrogyria is a malformation of cortical development. The aetiology of polymicrogyria remains poorly understood. Using whole-exome sequencing we found de novo heterozygous missense GRIN1 mutations in 2 of 57 parent-offspring trios with polymicrogyria. We found nine further de novo missense GRIN1 mutations in additional cortical malformation patients. Shared features in the patients were extensive bilateral polymicrogyria associated with severe developmental delay, postnatal microcephaly, cortical visual impairment and intractable epilepsy. GRIN1 encodes GluN1, the essential subunit of the N-methyl-d-aspartate receptor. The polymicrogyria-associated GRIN1 mutations tended to cluster in the S2 region (part of the ligand-binding domain of GluN1) or the adjacent M3 helix. These regions are rarely mutated in the normal population or in GRIN1 patients without polymicrogyria. Using two-electrode and whole-cell voltage-clamp analysis, we showed that the polymicrogyria-associated GRIN1 mutations significantly alter the in vitro activity of the receptor. Three of the mutations increased agonist potency while one reduced proton inhibition of the receptor. These results are striking because previous GRIN1 mutations have generally caused loss of function, and because N-methyl-d-aspartate receptor agonists have been used for many years to generate animal models of polymicrogyria. Overall, our results expand the phenotypic spectrum associated with GRIN1 mutations and highlight the important role of N-methyl-d-aspartate receptor signalling in the pathogenesis of polymicrogyria

Mitochondrial dysfunction in autism spectrum disorders: a systematic review and meta-analysis

A comprehensive literature search was performed to collate evidence of mitochondrial dysfunction in autism spectrum disorders (ASDs) with two primary objectives. First, features of mitochondrial dysfunction in the general population of children with ASD were identified. Second, characteristics of mitochondrial dysfunction in children with ASD and concomitant mitochondrial disease (MD) were compared with published literature of two general populations: ASD children without MD, and non-ASD children with MD. The prevalence of MD in the general population of ASD was 5.0% (95% confidence interval 3.2, 6.9%), much higher than found in the general population (∼0.01%). The prevalence of abnormal biomarker values of mitochondrial dysfunction was high in ASD, much higher than the prevalence of MD. Variances and mean values of many mitochondrial biomarkers (lactate, pyruvate, carnitine and ubiquinone) were significantly different between ASD and controls. Some markers correlated with ASD severity. Neuroimaging, in vitro and post-mortem brain studies were consistent with an elevated prevalence of mitochondrial dysfunction in ASD. Taken together, these findings suggest children with ASD have a spectrum of mitochondrial dysfunction of differing severity. Eighteen publications representing a total of 112 children with ASD and MD (ASD/MD) were identified. The prevalence of developmental regression (52%), seizures (41%), motor delay (51%), gastrointestinal abnormalities (74%), female gender (39%), and elevated lactate (78%) and pyruvate (45%) was significantly higher in ASD/MD compared with the general ASD population. The prevalence of many of these abnormalities was similar to the general population of children with MD, suggesting that ASD/MD represents a distinct subgroup of children with MD. Most ASD/MD cases (79%) were not associated with genetic abnormalities, raising the possibility of secondary mitochondrial dysfunction. Treatment studies for ASD/MD were limited, although improvements were noted in some studies with carnitine, co-enzyme Q10 and B-vitamins. Many studies suffered from limitations, including small sample sizes, referral or publication biases, and variability in protocols for selecting children for MD workup, collecting mitochondrial biomarkers and defining MD. Overall, this evidence supports the notion that mitochondrial dysfunction is associated with ASD. Additional studies are needed to further define the role of mitochondrial dysfunction in ASD

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems

Technology is transforming societies worldwide. A major innovation is the emergence of robotics and autonomous systems (RAS), which have the potential to revolutionize cities for both people and nature. Nonetheless, the opportunities and challenges associated with RAS for urban ecosystems have yet to be considered systematically. Here, we report the findings of an online horizon scan involving 170 expert participants from 35 countries. We conclude that RAS are likely to transform land use, transport systems and human–nature interactions. The prioritized opportunities were primarily centred on the deployment of RAS for the monitoring and management of biodiversity and ecosystems. Fewer challenges were prioritized. Those that were emphasized concerns surrounding waste from unrecovered RAS, and the quality and interpretation of RAS-collected data. Although the future impacts of RAS for urban ecosystems are difficult to predict, examining potentially important developments early is essential if we are to avoid detrimental consequences but fully realize the benefits